IEEE Digital Xplore Library Accepted · September 2024

Predictive Maintenance in Automotive using Machine Learning

This research applies advanced ML techniques for predictive maintenance in automotive systems to minimize unplanned downtime. High-frequency time-series sensor data from critical components like engines and brakes are analyzed using supervised learning models - Random Forest, SVM and LSTM. Data preprocessing (noise reduction and feature engineering) improves accuracy, while Grid Search and Cross-Validation tune hyperparameters. Feature importance is assessed via SHAP for interpretability.

The study uses Scikit-learn, TensorFlow and PySpark for training, with distributed computing on Apache Hadoop and Spark for large-scale data. Models are deployed on AWS Lambda for real-time failure prediction - demonstrating reduced failure risk, improved reliability and lower maintenance costs. Accepted for publication in the IEEE Journal, February 2025.

  • ISSN2169-3536
  • Manuscript IDAccess-2024-36520
  • PublisherIEEE Journal
  • StatusAccepted, September 2024
Int'l Journal of Applied Engineering & Technology December 2023

Optimizing Supply Chain Management Through Data Science and AI: A Data-Driven Approach

This research investigates the optimization of supply chain processes through advanced data analytics and machine learning. We focus on enhancing efficiency and resilience by employing predictive analytics over large-scale datasets, identifying operational bottlenecks and forecasting demand variability. The framework integrates statistical process control, ML algorithms and real-time data processing using Python, R and SQL.

A hybrid approach combining descriptive and prescriptive analytics evaluates supply chain performance - lead time, inventory turnover and order fulfillment. Case studies from manufacturing and logistics demonstrate the efficacy of data-driven decision-making, underscoring the importance of data integration, ML models and simulation in achieving supply-chain agility.

  • ISSN2633-4828
  • VolumeVol. 5, No. 4
  • PublisherIJAET
  • PublishedDecember 2023